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Author | SHA1 | Date | |
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bcaef53cbc | ||
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85e8493f4f |
4
.github/workflows/e2e.yml
vendored
4
.github/workflows/e2e.yml
vendored
@ -18,7 +18,9 @@ env:
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PYTHON_VERSION: "3.9"
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OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
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HATCH_VERSION: "1.14.1"
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HF_API_TOKEN: ${{ secrets.HUGGINGFACE_API_KEY }}
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# we use HF_TOKEN instead of HF_API_TOKEN to work around a Hugging Face bug
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# see https://github.com/deepset-ai/haystack/issues/9552
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HF_TOKEN: ${{ secrets.HUGGINGFACE_API_KEY }}
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jobs:
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run:
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@ -1 +1 @@
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2.15.0-rc0
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2.16.0-rc0
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@ -68,8 +68,8 @@ def test_ner_extractor_hf_backend(raw_texts, hf_annotations, batch_size):
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@pytest.mark.parametrize("batch_size", [1, 3])
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@pytest.mark.skipif(
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not os.environ.get("HF_API_TOKEN", None),
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reason="Export an env var called HF_API_TOKEN containing the Hugging Face token to run this test.",
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not os.environ.get("HF_API_TOKEN", None) and not os.environ.get("HF_TOKEN", None),
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reason="Export an env var called HF_API_TOKEN or HF_TOKEN containing the Hugging Face token to run this test.",
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)
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def test_ner_extractor_hf_backend_private_models(raw_texts, hf_annotations, batch_size):
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extractor = NamedEntityExtractor(backend=NamedEntityExtractorBackend.HUGGING_FACE, model="deepset/bert-base-NER")
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